STEM

Over the summer we chose a topic that interested us to incorporate into a STEM project. Then, from the beginning of the school year until February we worked on our project. Below are all of the details of my STEM1 project.

Mapping Arsenic Contamination of Drinking Water Across the United States

Overview

The incidence of drinking water contamination is increasing with urbanization throughout the United States and one of the main contaminants is arsenic. Arsenic can cause a host of health problems but continues to be found in water supplies; therefore, the goal of this project is to inform people that they may be at risk of consuming contaminated drinking water. Data about the coal power plants locations, retirement dates, and wind directions will be gathered. Then, the data will be mapped, and information about skin cancer in those areas will be compared to the spread of arsenic. The creation of this map will allow people to be more knowledgeable of when their drinking water is contaminated with arsenic.

Abstract

The incidence of drinking water contamination is increasing with urbanization throughout the United States, and one of the main contaminants is arsenic. Arsenic can cause a host of health problems but continues to be found in water supplies; therefore, the goal of this project is to inform people that they may be at risk of consuming contaminated drinking water. The first step of this project was to research and plot the 240 coal power plants in the US and to find the approximate wind directions in those locations. Then, using the wind directions and computer software such as javascript and mapbox, a distance of up to thirty miles from the power plants was plotted in the form of a heatmap. The predicted locations were then compared with health problems in those areas. Overall, melanoma of the skin, a common effect of arsenic poisoning, was a health problem found in abundance in each of the locations. Using Spearman's correlation as a statistical test it was concluded that the cases of skin cancer decreased as distance from the power plants increased. The statistical test showed that the data was significant because the average p value was around -1 which indicates a perfect negative association of ranks. This map is important because people living near coal power plants may be unaware that they need to test their drinking water for arsenic contamination. As a result, this map will show people if they are at risk of consuming contaminated drinking water.

Phrase 1

The incidence of drinking water contamination is increasing with urbanization throughout the United States and one of the main contaminants is arsenic.

Phrase 2

Arsenic can cause a host of health problems but continues to be found in water supplies; therefore, the goal of this project is to inform people that they may be at risk of consuming contaminated drinking water.

Background

Background

The incidence of drinking water contamination is increasing with urbanization throughout the United States and one of the main contaminants is arsenic. Places all over the world are plagued with contaminated drinking water. Since clean water is a necessity of life, it is imperative that everyone have access to uncontaminated water. Drinking water comes from two sources: surface waters and groundwater. These two sources of drinking water can get contaminated from a variety of circumstances: waste from industrial sites and runoff from agricultural land, chemical spills, badly located septic tanks, and local industries (Fawell & Nieuwenhuijsen, 2003). With the rising industrialization, drinking water contamination is becoming more pronounced.

There exist many contaminants of drinking water, but one very dangerous contaminant is arsenic. Arsenic poisoning can immediately cause muscle cramping, vomiting, abdominal pain, and death. Over a long period of time, arsenic poisoning can cause pigmentation changes, skin lesions, hard patches on the palms and soles of feet, cancers of the lungs, bladder, and skin, diabetes, and cardiovascular disease (“Arsenic”, n.d.). Despite the negative health conditions that arsenic poisoning can cause, arsenic is found in many locations, plaguing water supplies. Some hotspots for arsenic contamination are Bangladesh, Argentina, and Vietnam. Podgorski, an environmental scientist, and Berg, a hydrologist, created a map based on environmental factors to predict countries that may be at risk of arsenic contamination. The map shows that Asia and South America are expected to become hotspots for arsenic contamination (J. Podgorski and M. Berg, 2020). In addition to third world countries, wealthier places, like the United States, also have arsenic contaminated drinking water.

There exist many sources of arsenic, but one prominent source is coal power plants. When coal is burned, coal ash is produced and can be disposed of in a variety of ways such as in landfills or in waterways. Coal ash can be very dangerous if not properly monitored because it contains arsenic and can pollute waterways, groundwater, drinking water, and the air (“Coal Ash Basics”, 2020).

Additionally, the coal ash emitted from coal power plants can be carried downwind for about 30 miles, resulting in more severe air pollution (Fears, 2019). Arsenic, which is found in coal ash, will get carried downwind, contaminating the atmosphere in places surrounding coal power plants. Ecosystems can then be affected by air pollution which in turn, can cause water sources to be contaminated, resulting in an increased level of contamination (“Ecosystems and Air Quality”, 2020). As a result of the spread of air pollution, coal power plants can be major contributors to arsenic contaminated drinking water.

Arsenic contamination is a profound problem that people across the globe are faced with. Actions must be taken to protect against this contamination so as to prevent health problems and, in some cases, to prevent death. Since coal power plants can cause arsenic contaminated drinking water, it is important to know the locations near coal power plants that could be affected.

Procedure

Procedure

1. Research the locations of coal power plants

2. Determine the approximate wind direction in those locations.

3. Plot the coal power plant locations onto a map of the United States.

4. Determine locations that the wind from the coal power plants will reach. Those locations will be within 30 miles of the coal power plants.

5. Compare the mapped locations with health problems in those areas. Compare the distance from the power plants to skin cancer cases, using Spearman’s correlation to analyze the data.

6. Finalize the map so that it can be presented in a simple way to understand.

The Final Product

Jim Bridger Steam Plant

Bridger Plant Bridger Graph

Calculated P Values

Graph

Analysis

After the map was created, statistical analysis was used to determine the accuracy of the map. The specific test used was Spearman’s correlation because it measures the strength between two variables. In order to prove the accuracy of the map, the distance from the power plant and skin cancer rates in those areas were assessed. As a result, Spearman’s correlation was the best test since it could determine the strength of correlation between the distance from the power plants and skin cancer rates.

As seen from the table shown above, the Jim Bridger Steam Plant in Wyoming shows a sample of the data that was assessed when comparing the skin cancer cases with the distance from the power plant. The p value calculated for the Jim Bridger Steam Plant was -1 which indicates a perfect negative association of ranks, meaning that as the distance increases the amount of skin cancer cases increases. Beside the table is a graph displaying the decrease in cases as distance increases. The same statistical test was repeated for the other coal power plants and similar data was found.

The bottom table shows the p values that were calculated for each power plant. It is important to note that 23 of the power plants did not have any data about skin cancer rates available. As a result, those 23 power plants were subtracted from the total amount of power plants. Then, in order to determine the percent of each p value that was represented, the number of occurrences was put over the total power plants. As seen above, the p value that occured the most was -1. Each of the p values represent a different association between the 2 variables: -1 is a perfect negative association of ranks, and 1 is a perfect association of ranks. The closer the p value is to 0, the weaker the association is between the two variables, so when the p value is 0.5 or -0.5 it is much weaker and less relevant than when it is 1 or -1. Since -1 occurred the most, the statistical test shows that as the distance from the power plants increases, the amount of skin cancer cases decreases.

Discussion/Conclusion

Many people are at risk of drinking contaminated water but are unaware that they are experiencing this problem. In order for people to take the necessary precautions to ward against water contamination, they must be better informed. As a result, the map created will help inform them of any problems.

People drink water all throughout their day. They may be in an unfamiliar location and might be in search of water. If they are worried about contaminated drinking water or want to be reassured that the water is safe, they can check the arsenic prediction map. All that one has to do is type in the address, town, or city that they are in, and the map will zoom in on that location. If the area that was searched is within a blue triangle, then the water in that location might possibly be contaminated. If the area is in an unmarked space, then the drinking water is most likely not contaminated with arsenic produced from coal power plants.

This map was solely created based off wind data and the coal power plant locations. Since wind directions tend to shift, the map might not be accurate. In order to support the accuracy of the map, Spearman’s correlation was used. The results showed that the majority of the power plants followed the pattern in which as distance from the power plants increases, the skin cancer cases decrease. There were several outliers that might possibly contradict this conclusion but there are many variables in conditions that lead to these occurrences.

One of the main reasons for the outliers is that several power plants were occasionally located near or on top of each other. Since these power plants overlapped, the skin cancer cases tended to vary from the pattern. For example, when the wind direction heading from one power plant overlaps with another, the two areas of contamination overlap. The first power plant then would have skin cancer cases that would increase as the distance increases. This is caused from the overlap; since the second power plant starts in the area of contamination of the first, the cases caused by that plant are combined with the cases caused by the previous plant.

Another possible explanation for the variation in results of the statistical analysis is the causes of skin cancer. It has to be taken into account that skin cancer is not only caused by arsenic poisoning. One common source of skin cancer is excess contact with the sun. This cause was visible in locations where it tends to be warmer such as Florida. When researching the skin cancer data, some of the trends showed that skin cancer cases increased as distance from the beach decreased. This was seen when several of the power plants area of contamination was facing the ocean. Instead of the cases decreasing, they increased.

Another variable that had to be assessed while completing the statistical analysis was that some of the power plants had wind directions heading towards large bodies of water. Since the area of contamination was not affecting a location with people, no data could be collected about skin cancer cases. As a result, those power plants were ignored and data was collected about the remaining plants.

Overall, the map can be considered accurate because the majority of the p values were -1 which means that skin cancer cases decrease as distance from the power plants increase. As a result, this map can help people avoid drinking arsenic contaminated water. The map is very simple to use and will help increase knowledge of water contamination.

References

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February Fair Poster

Link to poster